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Econometric modelling of carbon dioxide emissions and concentrations, ambient temperatures and ocean deoxygenation
The Journal of the Royal Statistical Society, Series A (Statistics in Society) ( IF 2 ) Pub Date : 2021-07-15 , DOI: 10.1111/rssa.12732
Alok Bhargava 1
Affiliation  

This paper analysed several longitudinal data sets for investigating the dynamic inter-relationships between CO2 emissions and atmospheric concentrations, ambient temperatures and ocean acidification and deoxygenation. The methodological framework addressed issues such as the use of temperature ‘anomalies’, diffusion of CO2 to atmospheric stations, distributional misspecification and non-stationarity of errors affecting empirical models, and use of spline functions for modelling trends in temperatures. Longitudinal data on CO2 emissions for 163 countries and atmospheric CO2 concentrations at 10 stations, ambient temperatures from over 8,500 weather stations and seawater composition from over 380,000 oceanographic stations were analysed for 1985–2018 by estimating dynamic random effects models using maximum likelihood methods. The main findings were that CO2 emissions exhibited rapid upward trends at the country level, while minimum and maximum temperatures showed cyclical patterns; economic activity and population levels were associated with higher CO2 emissions. Second, there were gradual upward trends in annual and seasonal temperatures compiled at weather stations, and atmospheric CO2 concentrations were significantly associated with higher temperatures in the hemispheres. Third, there was a steady decline in dissolved oxygen levels, and the interactive effects of water temperatures and pH levels were significant. Overall, the results underscore the benefits of reducing CO2 emissions for ambient temperatures and for ocean deoxygenation. Synergies between CO2 emissions, ambient temperatures and ocean acidification are likely to exacerbate the melting of polar ice.

中文翻译:

二氧化碳排放和浓度、环境温度和海洋脱氧的计量经济学模型

本文分析了几个纵向数据集,用于研究 CO 2排放与大气浓度、环境温度和海洋酸化和脱氧之间的动态相互关系。该方法框架解决了诸如温度“异常”的使用、CO 2向大气站的扩散、分布错误指定和影响经验模型的误差的非平稳性以及使用样条函数模拟温度趋势等问题。163 个国家的 CO 2排放和大气 CO 2的纵向数据通过使用最大似然法估计动态随机效应模型,分析了 1985-2018 年 10 个站的浓度、8,500 多个气象站的环境温度和 380,000 多个海洋站的海水成分。主要调查结果是,CO 2排放量在国家层面呈现快速上升趋势,而最低和最高温度呈现周期性模式;经济活动和人口水平与较高的 CO 2排放量相关。其次,气象站编制的年度和季节温度呈逐渐上升趋势,大气 CO 2浓度与半球较高的温度显着相关。第三,溶解氧水平稳步下降,水温和pH值交互作用显着。总体而言,结果强调了减少 CO 2排放对环境温度和海洋脱氧的好处。CO 2排放、环境温度和海洋酸化之间的协同作用可能会加剧极地冰的融化。
更新日期:2021-07-15
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